make_plots: Plot and table of summary stats for continuous variables

Description Usage Arguments Value Examples

View source: R/make-eda-plots.R

Description

An opinionated function to plot exploratory data analysis (EDA) type information for an entire data frame, quickly and easily. Given a data frame or tibble, the function will create a plot/table combination depending on the class of the variable or column. Best use is to call this function within a RMarkdown file as part of the initial data exploration. This serves as documentation about the distributions of the variables in a data set.

Usage

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plot_cont(
  data,
  var,
  binw_select = "FD",
  subtitle = "Histogram (left), summary statistics (right)"
)

plot_categ(
  data,
  var,
  subtitle = paste0("Bar graph (left), ", "frequency table of top 5 levels (right)")
)

make_plots(df)

Arguments

data

A data frame or tibble

var

Variable or column name

binw_select

Specify method to calculate the bin width. "FD" for Freedman-Diaconis (1981) (default), "Sturges" for Sturges (1926), "Scott" for Scott (1979), "Square-root" for Square-root (N/A), or "Rice" for Rice (1944).

subtitle

String

df

A data frame or tibble

Value

A plot object

A plot object

A plot object

Examples

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library(ggplot2)
plot_cont(data = mtcars, var = disp)
plot_cont(data = mtcars, var = disp, binw_select = "Sturges")
plot_cont(data = mtcars, var = disp, binw_select = "Scott")
plot_cont(data = mtcars, var = disp, binw_select = "Rice")

ggplot(data = mtcars, aes(x = disp)) +
  geom_histogram()

ggplot(data = mtcars, aes(x = disp)) +
  geom_histogram(aes(y = ..density..), binwidth = 40) +
  geom_density()

library(dplyr)
library(ggplot2)
mt2 <- mtcars %>%
  mutate(cyl = factor(cyl))

plot_categ(data = mt2, var = cyl)
library(ggplot2)
make_plots(diamonds)

emilelatour/laviz documentation built on May 17, 2020, 3:44 a.m.